Application of Texture Analysis and Kohonen Map for Region Segmentation of Pavement Images for Crack Detection

The first phase of a research study on detecting cracks in pavements is described. For reliable crack detection, various regions in a road image have to be segmented accurately. A procedure based on the texture and color properties of different regions of images is used in conjunction with the Kohon...

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Bibliographic Details
Published in:Transportation research record 2012-01, Vol.2304 (1), p.150-157
Main Authors: Mathavan, S., Rahman, M. M., Kamal, K.
Format: Article
Language:English
Subjects:
Algorithms
Cracks
Flaw detection
Roads
Segmentation
Surface layer
Texture
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Summary:The first phase of a research study on detecting cracks in pavements is described. For reliable crack detection, various regions in a road image have to be segmented accurately. A procedure based on the texture and color properties of different regions of images is used in conjunction with the Kohonen map, also known as the self-organizing map. Accuracy of 89.7% was obtained with classification based on the Kohonen map of images taken with a regular digital camera and simple lighting setup. Furthermore, a complementary algorithm is described to remove spurious classifications caused by inaccuracies in the trained Kohonen map. With the help of this algorithm, an overall segmentation accuracy of 97.7% is reported. This research is expected to affect other problems in transportation engineering, such as road boundary detection and road marking inspection. The detection of cracks from the segmented regions will be addressed in the future.
ISSN:0361-1981
2169-4052
DOI:10.3141/2304-17